class_docstr: Construct a CoreML KNearestNeighborsClassifier specification.
  
  Please see the Core ML Nearest Neighbors protobuf message for more information
  on KNearestNeighborsClassifier parameters.
  
  Examples
  --------
  .. sourcecode:: python
  
      from coremltools.models.nearest_neighbors import KNearestNeighborsClassifierBuilder
      from coremltools.models.utils import save_spec
  
      # Create a KNearestNeighborsClassifier model that takes 4-dimensional input data and outputs a string label.
      >>> builder = KNearestNeighborsClassifierBuilder(input_name='input',
      ...                                              output_name='output',
      ...                                              number_of_dimensions=4,
      ...                                              default_class_label='default_label')
  
      # save the spec by the builder
      >>> save_spec(builder.spec, 'knnclassifier.mlmodel')
      
docstr: Ensure the label types matched the expected types.
  
  Parameters
  ----------
  spec
          The spec.
  
  labels
          The list of labels.
  
  Returns
  -------
  None, throws a TypeError if not expected.
docstr_tok: ["Ensure","the","label","types","matched","the","expected","types",".","Parameters","--","--","--","--","--","spec","The","spec",".","labels","The","list","of","labels",".","Returns","--","--","--","-","None",",","throws","a","TypeError","if","not","expected","."]
code: def _validate_label_types(self, labels):
      """
      Ensure the label types matched the expected types.
  
      Parameters
      ----------
      spec
              The spec.
  
      labels
              The list of labels.
  
      Returns
      -------
      None, throws a TypeError if not expected.
      """
      if self.spec.kNearestNeighborsClassifier.HasField(
          "int64ClassLabels"
      ):
          check_is_valid = (
              KNearestNeighborsClassifierBuilder._is_valid_number_type
          )
      else:
          check_is_valid = (
              KNearestNeighborsClassifierBuilder._is_valid_text_type
          )
      for label in labels:
          if not check_is_valid(label):
              raise TypeError(
                  "Invalid type for label: {}".format(type(label))
              )
  
imports: import numpy
  import coremltools
  from ...proto import FeatureTypes_pb2
  from ..None import datatypes
label_desc: Use image node_id 22 for calling the KNearestNeighborsClassifierBuilder obj's underlying member method code with example usage: obj._validate_label_types(labels) without return types